Generation and initial characterization of the prolactin-inducible protein (PIP) null mouse: accompanying global changes in gene expression in the submandibular glandThis article is one of a selection of papers published in a special issue celebrating the 125th anniversary of the Faculty of Medicine at the University of Manitoba.
Bibliographic record
Abstract
The human prolactin-inducible protein/gross cystic disease fluid protein-15 (hPIP/GCDFP-15) is a secretory glycoprotein found primarily in apocrine tissues including the breast and salivary glands. With largely unknown functions, PIP has been implicated in breast cancer and metastasis, host defense processes and T lymphocyte apoptosis. To begin to address PIP function in vivo, we generated the PIP null mouse (Pip-/-). Additionally, to determine the effect of the loss of PIP on gene expression and to gain insight into some of the molecular mechanisms underlying PIP function, microarray analysis of the submandibular gland was also undertaken. Pip-/- mice developed normally with no overt differences in behaviour or gross morphology and were fertile. However, histological examination of 3-month-old Pip-/- mice sometimes showed enlarged submandibular lymph nodes, lymphocytic aggregations within the prostate lobes, and enlarged medulla in the thymus. Functional analysis of gene expression revealed sets of multiple differentially expressed genes associated with cell death and survival, lipid metabolism, inflammation, immune disease, and cancer, as a consequence of mPIP abrogation. Taken together, these studies lend support to an immunomodulatory role for PIP in vivo and provide further insights into potentially novel signaling pathways and regulatory networks for PIP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".